HRIntelligencer v2.17

HRIntelligencer v2.17
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This week, we offer a smattering of insight and tutorial. Much if the work HR will be responsible is broader than the current definitions of the discipline. When jobs are rearranged, HR pulls the pieces together. When technology can hijack your mind, HR may want to learn how to motivate a workforce with it. When jobs are no longer the way we organize work, HR picks up the slack.

In the coming years, we are going to be tested as a discipline. Success will depend on seeing the issues as they advance and before they become crises. Here’s a glimpse.

 

Big Picture
  • The global logistics business is going to be transformed by digitization. From the Economist. Here’s a broad look at the way digital technologies are rearranging the pieces of the very traditional physical distribution business. From autonomous vehicles to self-organizing warehouses, all sorts of jobs are evolving to embrace smarter ways to do things. For example, if you can forecast demand, then you can reduce warehousing costs by using the shipping system as a warehouse. The key becomes knowing where stuff is rather than owning the place in which it is stored. The application of people to work can be similarly disaggregated.
  • Frontier AI: How far are we from artificial “general” intelligence, really? The hype is so intense that the scholarly AI community is afraid that the investors will withdraw and that this will be the start of the fourth time that AI development ground to a halt. It’s a shame that entrepreneurs have so little ability to differentiate their work that they resort to calling it AI.

 

HR’s View

 

Execution
  • Looking Beyond the Automation Debate. When it comes to automation in the workplace, it’s time to challenge the very concept of a job as the primary way to think about meaningful work. Accenture’s Eva Sage-Gavin weighs in.
  • Lobe.ai Build, train, and ship custom deep learning models using a simple visual interface. Execution can be deceptively simple. Watch the demo. Best 15 minutes you’ll spend this week.

 

Tutorial
  • MIT’s Artificial Intelligence Intro Course. All online. Great teacher. Great resources. Great price (free). I’m taking it.
  • Stochastic Process. Bookmark this Wikipedia definition. It’s a good short course in the sorts of non-linear process that characterize the way our organizations work. Stochastic processes are hard to automate.

 

Quote of the Week

“So, how far are we from AGI (Artificial General Intelligence)? This high-level tour shows contradictory trends. On the one hand, the pace of innovation is dizzying — many of the developments and stories mentioned in this piece (AlphaZero, new versions of GANs, capsule networks, RCNs breaking CAPTCHA, Google’s 2nd generation of TPUs, etc.) occurred just in the last 12 months, in fact mostly in the last 6 months. On the other hand, many the AI research community itself, while actively pursuing AGI, go to great lengths to emphasize how far we still are — perhaps out of concern that the media hype around AI may lead to dashed hopes and yet another AI nuclear winter.

Regardless of whether we get to AGI in the near term or not, it is clear that AI is getting vastly more powerful, and will get even more so as it runs on ever more powerful computers, which raises legitimate concerns about what would happen if its power was left in the wrong hands (whether human or artificial). One chilling point that Elon Musk was making the “Do you trust this computer?” documentary was that AI didn’t even need to want to be hostile to humans, or even know what humans are, for that matter. In its relentless quest to complete a task by all means, it could be harmful to humans just because they happened to be in the way, like a roadkill.

Leaving aside physical harm, progress in AI leads to a whole series of more immediate dangers that need to be thoroughly thought through — from significant job losses across large industries (back offices, trucking) to a complete distortion of our sense of reality (when fake videos and audio can be easily created).”

Bonus Quote of the Week:

Gender inequalities in the labour market start early. Even as babysitters, males are more likely to get a raise than females. And if there was an emotional connection between the female and the child, they were least likely to receive raises. One key issue in this frustrating situation is that women are more likely to be engaged in work which involves “emotional labour”.  (See also: books by women are priced 45% lower than books by men.)

 

About

Curate means a variety of things: from the work of vicar entrusted with the care of souls to that of an exhibit designer responsible for clarity and meaning. At the core, it means something about the importance of empathy in organization. HRIntelligencer is an update on the comings and goings in the Human Resource experiment with Artificial Intelligence, Digital Employees, Algorithms, Machine Learning, Big Data and all of that stuff. We present a few critical links with some explanation. The goal is to give you a way to surf the rapidly evolving field without drowning in information. We offer a timeless curation of the intersection of HR and the machines that serve it. We curate the emergence of Machine Led Decision Making in HR.